Unified Model in Identity Subspace for Face Recognition
Unified Model in Identity Subspace for Face Recognition作者机构：InstituteofComputingTechnologyTheChineseAcademyofSciencesBeijing100080P.R.China MultimediaInformationTechnologyTeachingCenterSchoolofInformationBeijingUniversityofPostsandTelecommunicationsBeijing100876P.R.China
出 版 物：《Journal of Computer Science & Technology》 (计算机科学技术学报（英文版）)
年 卷 期：2004年第19卷第5期
页 面：684-690页
核心收录：
学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程]
主 题：pattern recognition face recognition identity subspace unified model
摘 要：Human faces have two important characteristics: (1) They are similar objectsand the specific variations of each face are similar to each other; (2) They are nearly bilateralsymmetric. Exploiting the two important properties, we build a unified model in identity subspace(UMIS) as a novel technique for face recognition from only one example image per person. An identitysubspace spanned by bilateral symmetric bases, which compactly encodes identity information, ispresented. The unified model, trained on an obtained training set with multiple samples per classfrom a known people group A, can be generalized well to facial images of unknown individuals, andcan be used to recognize facial images from an unknown people group B with only one sample persubject, Extensive experimental results on two public databases (the Yale database and the Berndatabase) and our own database (the ICT-JDL database) demonstrate that the UMIS approach issignificantly effective and robust for face recognition.
维普期刊数据库